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@@ -44,6 +44,7 @@ def load_model(model_name):
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print(f"Loaded the model in {(time.time()-t0):.2f} seconds.")
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return model, tokenizer
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+# Removes empty replies from gpt4chan outputs
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def fix_gpt4chan(s):
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for i in range(10):
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s = re.sub("--- [0-9]*\n>>[0-9]*\n---", "---", s)
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@@ -52,7 +53,7 @@ def fix_gpt4chan(s):
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return s
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-def fn(question, temperature, max_length, inference_settings, selected_model):
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+def generate_reply(question, temperature, max_length, inference_settings, selected_model):
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global model, tokenizer, model_name, loaded_preset, preset
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if selected_model != model_name:
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@@ -70,7 +71,6 @@ def fn(question, temperature, max_length, inference_settings, selected_model):
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input_text = question
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input_ids = tokenizer.encode(str(input_text), return_tensors='pt').cuda()
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-
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output = eval(f"model.generate(input_ids, {preset}).cuda()")
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reply = tokenizer.decode(output[0], skip_special_tokens=True)
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@@ -86,7 +86,7 @@ else:
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default_text = "Common sense questions and answers\n\nQuestion: \nFactual answer:"
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interface = gr.Interface(
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- fn,
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+ generate_reply,
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inputs=[
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gr.Textbox(value=default_text, lines=15),
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gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='Temperature', value=0.7),
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@@ -98,7 +98,7 @@ interface = gr.Interface(
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gr.Textbox(placeholder="", lines=15),
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],
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title="Text generation lab",
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- description=f"Generate text using Large Language Models. Currently working with {model_name}",
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+ description=f"Generate text using Large Language Models.",
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)
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interface.launch(share=False, server_name="0.0.0.0")
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oobabooga